Research Article
Deep Learning-Based Efficient Model Development for Phishing Detection Using Random Forest and BLSTM Classifiers
Table 4
Performance results of the proposed model.
| Accuracy (%) | f1 score (%) | Precision (%) | True positive rate (%) | True negative rate (%) | False positive rate (%) | False negative rate (%) |
| 95.47 | 95.67 | 95.60 | 95.37 | 95.54 | 4.46 | 4.63 |
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